BACKGROUND:Impaired postural control is an important risk factor for falls and secondary damage in patients with idiopathic normal pressure hydrocephalus.Most of the existing studies have analyzed the gait parameters of patients during straight-line walking,but few have analyzed the postural stability characteristics of patients during static and dynamic activities. OBJECTIVE:To analyze the characteristics of postural stability in elderly patients with idiopathic normal pressure hydrocephalus. METHODS:Twenty-two patients clinically diagnosed with idiopathic normal pressure hydrocephalus at the Department of Neurosurgery,Huadong Hospital Affiliated to Fudan University,Shanghai,China,from September 2022 to February 2023 were selected as the patient group,and 18 healthy accompanying family members were selected as the healthy control group.The postural stability characteristics of the subjects were assessed using the Timed Up-and-Go Test,Multi-Directional Reach Test,Berg Balance Scale,and Static Balance Function Test(reaction time,speed of movement,directional control,maximum offset distance,and endpoint travel). RESULTS AND CONCLUSION:The time required to complete the Timed Up-and-Go Test was significantly longer in the patient group than in the healthy control group(P＜0.05).The results of the stretching test in the four directions of anterior,posterior,leftand right were significantly lower in the patient group than in the healthy control group(P＜0.05).The Berg Balance Scale scores in the patient group were lower than those in the healthy control group(P＜0.05).In the Static Balance Function Test,the results of reaction,movement speed,directional control,maximum offset distance and endpoint travel index were smaller in the patient group than the healthy control group(P＜0.05).To conclude,patients with idiopathic normal pressure hydrocephalus exhibit overall postural control deficits,and impaired reaction and execution abilities make these patients unable to make timely and accurate motor responses in the face of disturbances from internal or external sources,resulting in postural instability and increasing the risk of falls.

In recent years, the ongoing development of transcranial electrical stimulation (TES) and transcranial magnetic stimulation (TMS) has demonstrated significant potential in the treatment and rehabilitation of various brain diseases. In particular, the combined application of TES and TMS has shown considerable clinical value due to their potential synergistic effects. This paper first systematically reviews the mechanisms underlying TES and TMS, highlighting their respective advantages and limitations. Subsequently, the potential mechanisms of transcranial electromagnetic combined stimulation are explored, with a particular focus on three combined stimulation protocols: Repetitive TMS (rTMS) with transcranial direct current stimulation (tDCS), rTMS with transcranial alternating current stimulation (tACS), and theta burst TMS (TBS) with tACS, as well as their clinical applications in brain diseases. Finally, the paper analyzes the key challenges in transcranial electromagnetic combined stimulation research and outlines its future development directions. The aim of this paper is to provide a reference for the optimization and application of transcranial electromagnetic combined stimulation schemes in the treatment and rehabilitation of brain diseases.
Humans ; Transcranial Magnetic Stimulation/methods* ; Transcranial Direct Current Stimulation/methods* ; Brain Diseases/therapy*

Drug development remains a critical issue in the field of biomedicine. With the rapid advancement of information technologies such as artificial intelligence (AI) and the advent of the big data era, AI-assisted drug development has become a new trend, particularly in predicting drug-target associations. To address the challenge of drug-target prediction, AI-driven models have emerged as powerful tools, offering innovative solutions by effectively extracting features from complex biological data, accurately modeling molecular interactions, and precisely predicting potential drug-target outcomes. Traditional machine learning (ML), network-based, and advanced deep learning architectures such as convolutional neural networks (CNNs), graph convolutional networks (GCNs), and transformers play a pivotal role. This review systematically compiles and evaluates AI algorithms for drug- and drug combination-target predictions, highlighting their theoretical frameworks, strengths, and limitations. CNNs effectively identify spatial patterns and molecular features critical for drug-target interactions. GCNs provide deep insights into molecular interactions via relational data, whereas transformers increase prediction accuracy by capturing complex dependencies within biological sequences. Network-based models offer a systematic perspective by integrating diverse data sources, and traditional ML efficiently handles large datasets to improve overall predictive accuracy. Collectively, these AI-driven methods are transforming drug-target predictions and advancing the development of personalized therapy. This review summarizes the application of AI in drug development, particularly in drug-target prediction, and offers recommendations on models and algorithms for researchers engaged in biomedical research. It also provides typical cases to better illustrate how AI can further accelerate development in the fields of biomedicine and drug discovery.

Objective: To screen and identify the key active molecules, signaling pathways, and therapeutic targets of Shuxuening (SXN) injection for treating liver cirrhosis (LC) and to evaluate its therapeutic potential using a mouse model. Methods: Target genes of SXN and LC were retrieved from public databases, and enrichment analysis was performed. A protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and hub genes were identified using Molecular Complex Detection (MCODE). LC was induced in rats and mice via intraperitoneal injections of diethylnitrosamine and carbon tetrachloride (CCl4) for 12 weeks. Starting at week 7, SXN was administered intraperitoneally to the mice in the treatment group. Serum and liver tissues of the mice were collected for the detection of indicators, pathological staining, and expression analysis of hub targets using quantitative real-time polymerase chain reaction (qRT-PCR). Results: We identified 368 overlapping genes (OLGs) between SXN and LC targets. These OLGs were subsequently used to build a PPI network and to screen for hub genes. Enrichment analysis showed that these genes were associated with cancer-related pathways, including phosphoinositide-3-kinase/Akt and mitogen-activated protein kinase signaling and various cellular processes, such as responses to chemicals and metabolic regulation. In vivo experiments demonstrated that SXN treatment significantly improved liver function and pathology in CCl4-induced LC mice by reducing inflammation and collagen deposition. Furthermore, qRT-PCR demonstrated that SXN regulated the expression of MAPK8, AR and CASP3 in the livers of LC mice. Conclusion This study highlighted the therapeutic effects of SXN in alleviating LC using both bioinformatics and experimental methods. The observed effect was associated with modulation of hub gene expression, particularly MAPK8, and CASP3.

Traditional Chinese medicine (TCM) demonstrates distinctive advantages in disease prevention and treatment. However, analyzing its biological mechanisms through the modern medical research paradigm of "single drug, single target" presents significant challenges due to its holistic approach. Network pharmacology and its core theory of network targets connect drugs and diseases from a holistic and systematic perspective based on biological networks, overcoming the limitations of reductionist research models and showing considerable value in TCM research. Recent integration of network target computational and experimental methods with artificial intelligence (AI) and multi-modal multi-omics technologies has substantially enhanced network pharmacology methodology. The advancement in computational and experimental techniques provides complementary support for network target theory in decoding TCM principles. This review, centered on network targets, examines the progress of network target methods combined with AI in predicting disease molecular mechanisms and drug-target relationships, alongside the application of multi-modal multi-omics technologies in analyzing TCM formulae, syndromes, and toxicity. Looking forward, network target theory is expected to incorporate emerging technologies while developing novel approaches aligned with its unique characteristics, potentially leading to significant breakthroughs in TCM research and advancing scientific understanding and innovation in TCM.
Artificial Intelligence ; Medicine, Chinese Traditional ; Humans ; Network Pharmacology/methods* ; Drugs, Chinese Herbal/pharmacology* ; Animals ; Multiomics

To investigate the anti-atherosclerotic effects of dietary hesperidin and naringin on ather-osclerosis in rabbits.Twenty-four adult healthy male New Zealand Large White rabbits were ran-domly assigned to four groups based on one factor:control(Con),model(Mod),hesperidin(HP),and naringenin(NG),each containing six rabbits and housed in solitary cages.During the experi-mental period,the control group received normal feed;the model group was fed high-fat for 30 d to establish the atherosclerosis,(AS)model and continued to be fed high-fat feed;the hesperidin and naringenin groups were fed high-fat for 30 d and then underwent AS modeling,and at a later stage,150 mg of hesperidin(or naringenin)was added to the diets at a rate of 1.5 mg per kg of di-et,respectively,for 30 d.Relative body quality,blood lipids,oxidation,and inflammatory factor lev-els were all assessed.At the end of the test period,the test rabbits were sacrificed to obtain the common carotid artery for histopathological section HE staining,Oil red O staining,and Sirius red staining in order to observe vascular tissue structure,lipid and inflammatory cell infiltration,and e-lastic plate and elastic fiber damage.The results indicated that the relative body quality of the mod-el,HP and NG groups increased rapidly,and the difference with the control group within the same period was highly significant(P＜0.01);The HP and NG interventions significantly decreased to-tal cholesterol(TC)and low-density lipoprotein cholesterol(LDL-C)levels(P＜0.01),while also leading to a significant increase in high-density lipoprotein cholesterol(HDL-C)levels(P＜0.01);MDA levels exhibited a significant decrease(P＜0.01),while SOD levels showed a notable in-crease(P＜0.01)following the HP and NG interventions;After HP and NG interventions,TNF-α and IL-1 were regressed(P＜0.01)and IL-10 was significantly elevated(P＜0.01);Compared with the control group,the model group showed approximately 41.8 and 2.5 fold thickening of the maximal endo-medial membrane,respectively,and the HP and NG interventions showed approxi-mately 13 and 15 fold thickening of the maximal endo-medial membrane,and both of the maximal medial membranes thickened by approximately 1.4 fold;Staining of pathological sections showed that HP and NG intervened to significantly reduce inflammatory cell infiltration,deposition of lipid components,slight thickening of the endothelium,and intact fibroblastic components.The results showed that the addition of HP and NG to diets could regulate blood lipids and exert anti-inflam-matory and antioxidant effects by inhibiting the expression of inflammatory factors and oxidizing factors,showing significant anti-AS effects,and the two effects were comparable.

Objective To analyze the clinical efficacy and safety of Huoxue Xiaoyi decoction combined with exercise in the treatment of ovarian endometriosis.Methods 36 patients with ovarian endometriosis treated in Guang'anmen Hospital,China Academy of Chinese Medical Sciences from May 2022 to November 2022 were selected and treated with Huoxue Xiaoyi decoction combined with exercise for 3 months.The size of ovarian ectopic cyst,dysmenorrhea VAS score,PBAC score,female hormones,serum CA125 and CA199,catecholamines and cytokines levels were observed to evaluate the clinical efficacy and safety.Results After treatment,the maximum diameter of ovarian ectopic cyst,dysmenorrhea VAS score,PBAC score,cytokines(serum IL-1β,IL-2,IL-4,IL-6,IL-8,IL-10)levels were significantly lower than those before treatment(P<0.05).The levels of SHBG and adrenaline were significantly higher than those before treatment(P<0.05).During the treatment,the patient had no adverse drug reactions,vital signs,liver,and kidney function indexes were normal.Conclusion Huoxue Xiaoyi decoction combined with exercise therapy can reduce the size of ovarian ectopic cyst,relieve dysmenorrhea,regulate menstrual volume,increase the level of adrenaline,increase the level of sex hormone binding globulin,reduce the level of cytokines,and has fewer adverse reactions and good safety.

Objective To explore the mechanism by which the early growth response protein 1(EGR1)/AMP-activated protein kinase(AMPK)/nuclear factor erythroid 2-related factor 2(Nrf2)pathway improves Neuro-2a cell injury via Mendelian randomization(MR),bioinformatics and in vitro models of ischemic stroke(IS).Methods The blood proteins associated with genetic susceptibility to IS were identified based on MR analysis.Then,the GSE22255 dataset was comprehensively analyzed,including GSEA,immunoinfiltration and differential expression analysis.The transcription factors closely related to the occurrence and development of IS were identified after joint analysis with MR results,and the biological functions of key genes were further verified by in vitro experiments.Results A total of 712 proteins related to IS susceptibility were identified by MR analysis.A total of 2357 differentially expressed genes were identified from the GSE22255 dataset,and 75 intersection genes and 34 transcription factors were identified after combined analysis with MR results.In vitro experiments showed that knockdown of EGR1 expression could significantly inhibit oxygen-glucose deprivation/reperfusion(OGD/R)-induced Neuro-2a cell damage,and the mechanism might be related to the up-regulation of p-AMPK and Nrf2 protein expression.Conclusion This study integrates MR analysis,transcriptomics and in vitro experiments to reveal the potential role of 75 IS susceptibility genes and transcription factor EGR1 in the pathogenesis of IS,which provides theoretical basis for the development of therapeutic drugs for IS.

Objective To comprehensively evaluate the prevalence of and influencing factors for low-level viraemia(LLV)in Chinese patients receiving antiviral therapy for human immunodeficiency virus(HIV)infection through systematic review and Meta-analysis.Methods Cochrane Library,Web of Science,Embase,PubMed,China Bio-medicine(CBM),VIP,China National Knowledge Infrastructure(CNKI),and Wanfang Data were systematically retrieved.Retrieval time was from the establishment of the database to February 2024.Literatures related to the prevalence of LLV in patients receiving antiviral therapy for HIV infection were retrieved using combination of key-words and free words.Stata 16.0 software was used for Meta-analysis.Random effects model was adopted to calcu-late the combined prevalence and its 95％confidence interval.Results A total of 15 papers were included in analy-sis,involving 191 212 specimens.Meta-analysis random effects model showed that the prevalence of LLV in Chinese patients receiving antiviral therapy for HIV infection was 13.00％(95％CI:7.82％-19.24％).Subgroup analysis showed that cross-sectional studies,northern regions,males,age ≥50 years,heterosexual transmission routes,baseline CD4+T lymphocyte count＜200 cells/μL,and patients who had ever changed therapy regimens had higher LLV prevalence.Conclusion The prevalence of LLV in patients receiving antiviral therapy for HIV infection is re-latively higher.Attention should be paid to such high-risk population,and appropriate antiviral therapy schemes should be selected as early as possible.Timely intervention is necessary when LLV occurs.

Meat food is an important part of people's dietary supplements,but in recent years,meat adulteration cases are hidden and frequent,which seriously affects people's health and destroys the fairness of the market.Based on this,this paper analyses the development trend of meat adulteration and the current meat adulteration detection technology is summarized,combed in detail the use of the most widely used real-time fluorescence quantitative PCR technology application of the status quo and challenges to help real-time fluorescence quantitative PCR technology testing in meat adulteration evidence testing to the direction of more high detection efficiency and higher accuracy development.